Abstract
In biometrics, template protection aims to protect the confidentiality of templates (i.e., enrolled biometric data) by certain conversion. At ACNS 2015, as a new approach of template protection, Takahashi et al. proposed a new concept of digital signature, called “fuzzy signature”, that uses biometric data as a private key for securely generating a signature. After that, at ACNS 2016, Matsuda et al. modified the original scheme with several relaxing requirements. A main ingredient of fuzzy signature is “linear sketch”, which incorporates a kind of linear encoding and error correction process to securely output only the difference of signing keys without revealing any biometric data. In this paper, we give recovering attacks against the linear sketch schemes proposed at ACNS 2015 and 2016. Specifically, given encoded data by linear sketch (called a “sketch”), our attacks can directly recover both the signing key and the biometric data embedded in the sketch. Our attacks make use of the special structure that a sketch has the form of a sum of an integral part and a decimal part, and biometric data is embedded in the decimal part. On the other hand, we give a simple countermeasure against our attacks and discuss the effect in both theory and practice.
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References
Belguechi, R., Alimi, V., Cherrier, E., Lacharme, P., Rosenberger, C.: An overview on privacy preserving biometrics. In: Yang, J. (ed.) Recent Application in Biometrics. InTech (2011)
Dodis, Y., Reyzin, L., Smith, A.: Fuzzy extractors: how to generate strong keys from biometrics and other noisy data. In: Cachin, C., Camenisch, J.L. (eds.) EUROCRYPT 2004. LNCS, vol. 3027, pp. 523–540. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24676-3_31. Full version in SIAM J. Comput. 38(1), 97–139 (2008)
Jain, A.K., Nandakumar, K., Nagar, A.: Biometric template security. EURASIP J. Adv. Signal Process. 2008, 113:1–113:17 (2008). http://dx.doi.org/10.1155/2008/579416
Juels, A., Sudan, M.: A fuzzy vault scheme. Des. Codes Crypt. 38(2), 237–257 (2006)
Juels, A., Wattenberg, M.: A fuzzy commitment scheme. In: Proceedings of the 6th ACM Conference on Computer and Communications Security, pp. 28–36. ACM (1999)
Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition, 2nd edn. Springer, Heidelberg (2009)
Matsuda, T., Takahashi, K., Murakami, T., Hanaoka, G.: Fuzzy signatures: relaxing requirements and a new construction. In: Manulis, M., Sadeghi, A.-R., Schneider, S. (eds.) ACNS 2016. LNCS, vol. 9696, pp. 97–116. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39555-5_6
Schnorr, C.P.: Efficient signature generation by smart cards. J. Cryptology 4(3), 161–174 (1991)
Sutcu, Y., Sencar, H.T., Memon, N.: A secure biometric authentication scheme based on robust hashing. In: Proceedings of the 7th Workshop on Multimedia and Security, pp. 111–116. ACM (2005)
Takahashi, K., Matsuda, T., Murakami, T., Hanaoka, G., Nishigaki, M.: A signature scheme with a fuzzy private key. In: Malkin, T., Kolesnikov, V., Lewko, A.B., Polychronakis, M. (eds.) ACNS 2015. LNCS, vol. 9092, pp. 105–126. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-28166-7_6
Teoh, A.B., Goh, A., Ngo, D.C.: Random multispace quantization as an analytic mechanism for biohashing of biometric and random identity inputs. IEEE Trans. Pattern Anal. Mach. Intell. 28(12), 1892–1901 (2006)
Waters, B.: Efficient identity-based encryption without random oracles. In: Cramer, R. (ed.) EUROCRYPT 2005. LNCS, vol. 3494, pp. 114–127. Springer, Heidelberg (2005). https://doi.org/10.1007/11426639_7
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Yasuda, M., Shimoyama, T., Takenaka, M., Abe, N., Yamada, S., Yamaguchi, J. (2017). Recovering Attacks Against Linear Sketch in Fuzzy Signature Schemes of ACNS 2015 and 2016. In: Liu, J., Samarati, P. (eds) Information Security Practice and Experience. ISPEC 2017. Lecture Notes in Computer Science(), vol 10701. Springer, Cham. https://doi.org/10.1007/978-3-319-72359-4_24
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DOI: https://doi.org/10.1007/978-3-319-72359-4_24
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